Diagnostic analysis of a circular-circular regression model using asymmetric or asymmetric bi-modal circular errors.

Many circular data sets encountered in practice are asymmetric or asymmetric bi-modal. In this paper, we propose a diagnostic analysis of a parametric circular regression model with a single circular explanatory variable by assuming asymmetric or asymmetric bi-modal circular errors. We develop a new test statistic for detecting outliers both in circular response and explanatory variables. For the case with a circular explanatory variable, we employ a parametric inverse circular-circular regression model. In addition, we provide a goodness of fit test to find whether circular errors are symmetric or not. Our methods are illustrated using a real data set arising from a study of Genomics. [ABSTRACT FROM AUTHOR]